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一种用于自动定量斑马鱼幼体中细菌负荷的图像处理工具。

An Image Processing Tool for Automated Quantification of Bacterial Burdens in Zebrafish Larvae.

作者信息

Yamaguchi Naoya, Otsuna Hideo, Eisenberg-Bord Michal, Ramakrishnan Lalita

机构信息

Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CB2 0AW Cambridge, UK.

MRC Laboratory of Molecular Biology, CB2 0QH Cambridge, UK.

出版信息

bioRxiv. 2024 Aug 19:2024.08.16.608298. doi: 10.1101/2024.08.16.608298.

Abstract

Zebrafish larvae are used to model the pathogenesis of multiple bacteria. This transparent model offers the unique advantage of allowing quantification of fluorescent bacterial burdens (fluorescent pixel counts: FPC) in vivo by facile microscopical methods, replacing enumeration of bacteria using time-intensive plating of lysates on bacteriological media. Accurate FPC measurements require laborious manual image processing to mark the outside borders of the animals so as to delineate the bacteria inside the animals from those in the culture medium that they are in. Here, we have developed an automated ImageJ/Fiji-based macro that accurately detect the outside borders of -infected larvae.

摘要

斑马鱼幼体被用于多种细菌致病机制的建模。这种透明模型具有独特优势,即通过简便的显微镜方法能够在体内对荧光细菌负荷(荧光像素计数:FPC)进行定量,取代了在细菌培养基上对裂解物进行耗时铺板来计数细菌的方法。准确的FPC测量需要费力的手动图像处理来标记动物的外部边界,以便将动物体内的细菌与它们所处培养基中的细菌区分开来。在此,我们开发了一种基于ImageJ/Fiji的自动化宏程序,可准确检测受感染幼体的外部边界。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a82a/11370481/d3690c743a4c/nihpp-2024.08.16.608298v1-f0001.jpg

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